Paul Seiferth is affiliated with the Department of Computer Science at Freie Universität Berlin. His research focuses on computational geometry, algorithms, data structures, and graph theory. He has contributed to topics like Voronoi diagrams, dynamic planar graphs, unit disk routing, and spanner construction. His work emphasizes algorithmic efficiency, time-space trade-offs, and geometric data structures. Education : PhD (2012–2016), Freie Universität Berlin Master's (2010–2012), Freie Universität Berlin Research Interests : His research addresses fundamental problems in computational geometry and graph theory, with applications to wireless networks and geometric algorithms. Key themes include dynamic data structures for proximity problems (e.g., Voronoi diagrams), routing in unit disk graphs, and efficient spanner constructions for directed transmission graphs. Key Contributions : His work on time-space trade-offs for Voronoi diagrams and dynamic planar Voronoi diagrams has advanced algorithmic techniques for geometric problems. He also developed efficient routing schemes for unit disk graphs and reachability oracles for transmission graphs, balancing theoretical guarantees with practical efficiency. Teaching : He teaches ProInformatik I: Logik und Diskrete Mathematik . Labs/Teams : Associated with the AG Theoretische Informatik research group at Freie Universität Berlin.
Karl-Theodor Sturm is a Full Professor at the Institute for Applied Mathematics of the University of Bonn, where he has been since 1997. His research focuses on Stochastic Analysis , Geometric Analysis , and Metric Measure Spaces , particularly in the context of Ricci Curvature , Optimal Transport , and Liouville Quantum Gravity . He currently serves as Director of the Hausdorff Research Institute for Mathematics (since 2024) and previously coordinated the Hausdorff Center for Mathematics (2012–2019). As Principal Investigator of the ERC Advanced Grant Metric measure spaces and Ricci curvature - analytic, geometric and probabilistic challenges (2016–2022), he advanced interdisciplinary research at the intersection of geometry, probability, and analysis. Research Themes : Synthetic Ricci curvature, Optimal transport, Stochastic analysis on singular and random spaces, Dirichlet forms, Geometric inequalities. Recent Publications : Highlighted works include studies on heat flows on nonconvex domains, Wasserstein diffusions, and conformally invariant random fields in quantum gravity. His work often bridges probabilistic methods with geometric and analytic structures. Scientific Awards : Notable accolades include the Heisenberg Fellowship of the DFG (1994) and the ERC Advanced Grant (2016–2022). He has declined offers from prestigious institutions like Imperial College London, Northwestern University, and the University of Kansas. Teaching and Leadership : He leads graduate seminars (e.g., on Gaussian Free Fields and Liouville Quantum Gravity) and advanced courses in geometric analysis. As Managing Director of his institute and member of scientific committees (e.g., Mathematische Forschungsinstitut Oberwolfach), he shapes academic governance.
Hartmut Löwen is a Professor and Chair at the Institute of Theoretical Physics II - Soft Matter at Heinrich Heine University Düsseldorf, where he has held a professorship since 1995. His research spans multiple areas of theoretical physics with a particular focus on soft matter systems and statistical physics. He has served in numerous leadership roles including as Coordinator of the Sonderforschungsbereich TR6 (2002-2013), Coordinator of the German-Japanese bilateral cooperation on Soft Matter in nonequilibrium (2011-2013), and as a member of the Senate of the Deutsche Forschungsgemeinschaft (2014-2021). 1982-1986: Study of physics, mathematics and chemistry at University of Dortmund 1987: PhD in physics on Phase transitions in polaron systems at University of Dortmund 1988-1990: Postdoc at Ludwig-Maximilians-Universität München 1990-1991: Postdoc at Ecole Normale Supérieure de Lyon 1991-1995: Postdoc at Ludwig-Maximilians-Universität München 1993: Habilitation at Ludwig-Maximilians-Universität München Löwen's research focuses on structure, dynamics and phase transitions in colloidal suspensions, collective behavior of active particles, statistical mechanics of interfaces, nonequilibrium phenomena, glass transition, nucleation, computer simulations, density functional theory, polymers, polyelectrolytes and liquid crystals, biological physics including bacterial motility and protein crystallization, and dusty plasmas. His work bridges theoretical physics with experimental collaborations across multiple international institutions. His recent publications (2023-2025) demonstrate a strong focus on active matter systems, with particular emphasis on non-equilibrium dynamics, phase transitions in active systems, and the thermodynamics of self-propelled particles. The publications reveal a consistent pattern of interdisciplinary research that connects statistical physics with soft matter, biophysics, and materials science, often through collaborations with experimental groups to validate theoretical predictions. SigmaPhi Prize for seminal contributions to Statistical Physics (2023) Fellow of the Institute of Physics (since 1999) Gentner-Kastler-Prize (2003) ERC Advanced Grant INTERCOCOS (2010) Heisenberg-fellowship of the Deutsche Forschungsgemeinschaft (1994) Selected as Outstanding Referee for Physical Review journals (2017) Löwen has successfully secured significant research funding including the ERC Advanced Grant INTERCOCOS and leadership roles in multiple DFG-funded priority programs including SPP 1726 on microswimmers and SPP 1296 on heterogeneous nucleation. His current research group maintains active collaborations with institutions across Europe, Japan, and the United States, focusing on both theoretical development and experimental validation of models in soft matter physics. He has supervised numerous PhD students and postdoctoral researchers who have gone on to establish careers in academia and industry. Löwen leads a vibrant research group focused on theoretical soft matter physics with connections to multiple experimental collaborations. His group participates in the Science Priority Program SPP 2265 'Random geometric systems' of the DFG and the ITN Active Matter of the EU, maintaining active partnerships with researchers studying complex plasmas, liquid crystalline phases, microgel particles, active colloidal particles, and breathing particles.
Christian Kühn is a Full Professor at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology. His research bridges differential equations, dynamical systems, and mathematical modeling, with emphasis on multiscale problems, stochastic effects, and adaptive networks. Phenomena of interest include pattern formation, bifurcations, and scaling laws. Education: BSc in Mathematics, Jacobs University Bremen (2005) M.A.St., University of Cambridge (2006) PhD in Applied Mathematics, Cornell University (2010) His work integrates analytical rigor with applications across physics, biology, and engineering. Key themes involve geometric singular perturbation theory, critical transitions in complex systems, and noise-driven dynamics. Publications consistently explore hierarchical temporal structures and universal mechanisms in nonlinear phenomena. Awards: Richard-von-Mises Prize (2017) Lichtenberg Professorship (2016) Best Paper Award, TU Vienna (2014) Leibniz Fellowship (2013) APART Fellowship (2012)
Professor Gaëtan Borot is a faculty member at the Institute of Mathematics, Faculty of Mathematics and Natural Sciences, Humboldt-Universität zu Berlin. He leads a research group in Mathematical Physics with connections to quantum field theory, string theory, and geometric analysis. His work is supported by multiple Research Training Groups including Rethinking QFT (2019-2029), From geometry to numbers (2024-2029), and the College of Mathematics and Physics Berlin (2020-2029). Professor Borot's research centers around topological recursion and its applications across mathematical physics. His work connects enumerative geometry, quantum algebra, moduli spaces, and random matrix theory through a unifying framework that reveals deep connections between seemingly disparate fields. He investigates how topological recursion provides methods to study quantization of geometric objects and field theories, with applications ranging from Gromov-Witten theory to statistical physics models on random surfaces. Analysis of his recent publications (2021-2024) shows a strong focus on the mathematical structures underlying conformal field theories, particularly Liouville CFT, where he explores Virasoro representations, scattering matrices, and equations of motion. His work on topological recursion continues to expand into new domains including cohomological field theories, Hurwitz theory, and spectral curves, demonstrating the versatility of this algebraic structure across mathematical physics. Professor Borot actively supervises PhD students including Giacomo Umer (who successfully defended in May 2025), Davide Scazzuso, and Niklas Martensen, along with numerous master's and bachelor's students. He organizes the Mathematical Physics Seminar held weekly in Adlershof and has taught courses on integrable systems, random matrix theory, and differential geometry. Despite currently being on leave until September 2025, he continues to supervise thesis projects with availability starting October 2025.
Prof. Dr. Sabine Jansen is a Professor at the Mathematical Institute of LMU Munich and leads the Working Group on Stochastics and Financial Mathematics . Her research spans Probability Theory , Quantum Statistical Mechanics , and Mathematical Physics , with a focus on cluster expansions, Gibbs point processes, and duality for Markov processes. Email: jansen@math.lmu.de Phone: +49 (0)89 2180 4477 Address: Theresienstr. 39, D-80333 Munich Affiliations: DFG Collaborative Research Center CRC TRR 352, DFG Priority Program SPP2265, Munich Center for Quantum Science and Technology (MCQST) Her research interests include: Stochastic processes and their applications in financial mathematics Quantum statistical mechanics, particularly many-body systems and their collective phenomena Cluster expansions and virial inversion for low-temperature and non-additive systems Duality and intertwining relations in Markov processes Combinatorial approaches to probability and statistical mechanics Recent publications highlight work on: Large deviations and extreme value theory for Weibull-like variables Algebraic methods in continuum particle systems Geometric constraints in hard-particle mixtures Convergence conditions for cluster expansions Quantum quasi-1D jellium and Coulomb systems Applications of Lagrange inversion in combinatorial species She contributes to educational resources through lecture notes and courses, including topics like Quantum mechanics for probabilists and Jump processes . Her group collaborates with international institutions and participates in major research programs.
Yuedong Yang is a Professor at the School of Data and Computer Science, Sun Yat-sen University since August 2017. His academic journey includes a Research Assistant Professor position at Indiana University (2011-2013) and Research Fellow at Griffith University's Institute for Glycomics (2013-2017), following postdoctoral training at Indiana University School of Medicine (2006-2011). His primary research focuses on Protein Structure Prediction and Refinement , Protein Interactions with biomolecules and ligands, and Classification of Human Genetic Variations . His work bridges computational biology, machine learning, and structural bioinformatics, with emphasis on developing AI-driven methods for biomolecular analysis. Recent publications demonstrate strong integration of geometric deep learning, language models, and physics-based approaches. Analysis of his 15 most recent publications (2024-2025) reveals dominant trends in spatial transcriptomics , protein structure-function prediction , foundation models for genomics , and interpretable AI for drug discovery . His work increasingly combines multimodal data integration with causal learning frameworks. Over 50 publications in top journals including PNAS, Genome Biology, Nucleic Acids Research, and Bioinformatics Active community service as Associate Editor for BMC Bioinformatics Extensive peer review activity across 46 publications/grants in 35+ journals His research is supported by multiple major grants including National Natural Science Foundation of China (61772566), National Health and Medical Research Council (1121629), and Australian Research Council (LP150100137). He has advised numerous researchers through collaborative projects in computational biology and bioinformatics. Dr. Yang leads research in protein informatics and multi-omics integration, with current projects focusing on geometric deep learning for biomolecular structure prediction and foundation models for single-cell genomics. His lab maintains strong international collaborations between China, USA, and Australia.
Dr. Lars Krecklau is a researcher at the Department of Computer Science , RWTH Aachen University . He specializes in procedural modeling, real-time rendering, and urban reconstruction. His work includes algorithms for efficient 3D visualization of cityscapes and interactive modeling tools for non-programmers. Research Focus : Procedural modeling, real-time rendering, urban visualization Key Contributions : Procedural facade rendering, historical city interpolation, interconnected structure modeling His publications focus on GPU-accelerated procedural graphics, temporal interpolation of historical data, and intuitive 3D modeling interfaces. He has contributed to frameworks like Houdini and developed techniques for memory-efficient rendering. Email : krecklau@informatik.rwth-aachen.de
Prof. Dr. Sabine Jansen is a faculty member at the Mathematical Institute of Ludwig Maximilian University of Munich (LMU) . Her research focuses on stochastic processes, statistical mechanics, and quantum systems, particularly through her work in cluster expansions, Gibbs measures, and random geometric systems. She is affiliated with the Working Group on Stochastics and Financial Mathematics and participates in the DFG Collaborative Research Center CRC TRR 352 ( Mathematics of many-body quantum systems and their collective phenomena ) and the DFG priority program SPP2265 ( Random Geometric Systems ). Her office is located at Theresienstr. 39, 80333 Munich (Room 214, Block B, 2nd floor), and she can be contacted at Sabine.Jansen@math.lmu.de or jansen@math.lmu.de . Key Research Areas : Stochastic processes, cluster expansions, quantum statistical mechanics, many-body systems, and probabilistic methods in mathematical physics. Notable Collaborations : DFG-funded projects (CRC TRR 352, SPP2265), Munich Center for Quantum Science and Technology (MCQST), and international collaborations with institutions like Leiden University. Publications : Recent work includes studies on large deviations, intertwinings for continuum systems, virial inversion, and combinatorial approaches to generating functions. Labs & Teams : Leads the Stochastics and Financial Mathematics working group, contributing to quantum systems research at LMU and MCQST.
Colin Jahel is a Research Fellow at Technische Universität Dresden, specializing in mathematical research at the intersection of Model Theory, Dynamics, and Probability Theory. He completed his PhD in 2021 at the University of Lyon, France, under the supervision of Lionel Nguyen Van Thé and Todor Tsankov. Prior to his current position, he was a postdoctoral researcher at Carnegie Mellon University. His research explores connections between model-theoretic methods and dynamical systems, with emphasis on invariant measures, automorphism groups, and structural properties of mathematical objects. Key themes include ergodic theory applications to countable structures, topological dynamics of Polish groups, and probabilistic aspects of mathematical logic. Jahel's publications demonstrate consistent focus on interactions between model theory and dynamics, with recurrent themes of invariant measures, group actions, and classification of infinite structures. His collaborative work frequently addresses problems in geometric group theory, combinatorial limit theory, and measurable dynamics. He maintains active research collaborations with mathematicians across institutions, including co-authors from Carnegie Mellon University, Charles University, and other European universities.
Andrej Bogdanov is a Professor in the Department of Computer Science at the Weizmann Institute of Science's Faculty of Mathematics and Computer Science. With a prolific publication record spanning over two decades from 2002 to 2025, he has established himself as a leading researcher in theoretical computer science and cryptography. His research interests span multiple areas of theoretical computer science, with a particular focus on cryptography, computational complexity, pseudorandomness, and secret sharing. His work often bridges theoretical foundations with practical cryptographic applications, exploring the mathematical underpinnings of secure computation and cryptographic primitives. His research has evolved to address contemporary challenges in quantum computing security and machine learning evaluation. Bogdanov's publication record shows consistent contributions to top-tier conferences including FOCS, STOC, CRYPTO, TCC, and ITCS. His work demonstrates deep theoretical insights while maintaining relevance to practical cryptographic applications. Recent publications indicate expanding interests into quantum computing security and machine learning evaluation frameworks. Bogdanov has collaborated extensively with leading researchers in theoretical computer science, most notably with Alon Rosen (31 joint publications), as well as Siyao Guo, Yuval Ishai, and Chin Ho Lee. His collaborative work spans multiple institutions and reflects the interdisciplinary nature of modern theoretical computer science research. His academic contributions include foundational work on pseudorandom generators, secret sharing schemes, hardness amplification, and more recently, contributions to post-quantum cryptography and quantum security. His research has been supported by multiple grants that have enabled his team to explore the theoretical boundaries of cryptographic security.
Luciano Spinello is a Research Fellow affiliated with the University of Freiburg's Department of Computer Science, working within the AIS Lab led by Prof. W. Burgard. Previously, he held roles at Amazon Research (Seattle), ETH Zurich (PhD under Prof. Roland Siegwart), and EPFL Lausanne as a research assistant. His research focuses on the intersection of computer vision and robotics, specializing in robot perception, SLAM, and autonomous systems. He has contributed to projects involving RGB-D data processing, terrain classification, and socially-aware navigation algorithms. Education: PhD in Computer Science from ETH Zurich (2009), Electrical Engineering degree from Rome, Italy. Academic activities include organizing workshops (RSS 2014, IROS 2012), serving on program committees for robotics conferences, and editorial roles (IROS associate editor). His work emphasizes multimodal sensing, object detection in 3D environments, and robust localization across dynamic conditions. Key technical contributions include methods for RGB-D fusion, adaptive domain adaptation, and large-scale place recognition. His research bridges theoretical advancements with practical applications in autonomous robotics, including navigation systems and human-robot interaction protocols.
Prof. Werner Martin is a Professor of Big Geospatial Data Management at the Technical University of Munich (TUM), affiliated with the School of Engineering and Design and the Department of Aerospace and Geodesy. His research focuses on georeferenced data processing, distributed computing, quantum algorithms, and machine learning applications in geospatial contexts. Prof. Martin holds a doctorate from LMU Munich and has held academic and research positions at institutions including LMU Munich, Leibniz-University Hannover, the German Aerospace Center (DLR), and UniBW Munich. His work bridges theoretical advancements with practical applications in spatial data analysis, visualization, and high-performance computing. Awards ACM SIGSPATIAL GIS Certificate of Appreciation (2019) 1st place ACM SIGSPATIAL GIS Cup (2015) IPIN Best Paper Award (2014) His recent publications emphasize geospatial AI, quantum computing for data processing, and environmental monitoring systems. Collaborations with industry partners like DLR highlight his focus on real-world geospatial challenges.
Torsten Mütze is a Professor at the Institute of Mathematics at the University of Kassel. Previously, he held positions as an Assistant Professor at the University of Warwick (2019–2024) and was affiliated with Charles University Prague's Department of Theoretical Computer Science and Mathematical Logic. His academic journey includes a postdoc under Martin Skutella at TU Berlin, research stays at Georgia Tech and ETH Zurich, and a software engineering role at Supercomputing Systems Zurich. Education: PhD in 2011 from ETH Zurich under Angelika Steger's supervision Master's and Bachelor's degrees in related fields Research Interests: Focuses on discrete mathematics and theoretical computer science, including combinatorial algorithms, graph theory, computational geometry, order theory, Ramsey theory, and combinatorial games. His work bridges foundational theory and real-world applications, particularly in algorithm design and combinatorial generation. Advising & Grants: Supervised students: Francesco Verciani, Nastaran Behrooznia, Namrata, Arturo Merino, Frieder Smolny, Karl Däubel, Jerri Nummenpalo, and Ondřej Mička Funded projects: DFG Heisenberg grant 522790373, Chancellor's International Scholarships, and EU funding Labs & Collaborations: Organizes workshops like 'Combinatorics, Algorithms and Geometry' and contributes to research networks such as the 'Combinatorial Optimization and Graph Algorithms' group. His work involves collaborations with institutions globally, including ETH Zurich, Georgia Tech, and TU Berlin.
Alex Black is currently a Hermann Weyl Instructor at ETH Zurich, focusing on algebraic and geometric combinatorics and optimization. He will join Bowdoin College as a tenure-track assistant professor in the mathematics department starting Fall 2025. His research emphasizes the simplex method and its applications in optimization and polytope theory. Black’s research explores the interplay between algebraic and geometric combinatorics, with a particular focus on optimization and the simplex method. His work addresses topics such as polytopes, matroid theory, and pivot rules, aiming to advance understanding in discrete and computational geometry. He investigates issues like exponential lower bounds for pivot rules, monotone paths on polytopes, and the structure of flag polymatroids. INFORMS 2022 George Nicholson Paper Competition Finalist for Small Shadows of Lattice Polytopes No advising roles or grants are explicitly mentioned in the provided information.
